Motion planning for a formation of autonomous robots

Authors

  • Maira Estefanía Pereyra, Doctoranda Centro de Investigación en Informática para la Ingeniería (CIII), Facultad Regional Córdoba, Universidad Tecnológica Nacional – Argentina
  • R. Gastón Araguás Director
  • Gonzalo Pérez Paina Codirector
  • Miroslav Kulich Codirector

DOI:

https://doi.org/10.33414/ajea.5.698.2020

Keywords:

Genetic Algorithm, A* algorithm, path planning, evolutive operators, mobile robot, Voronoi diagram, transition states graph, multirobots

Abstract

In this work the latest research results are presented within the framework of the thesis Motion planning for a formation of autonomous robots. Path planning is the task of finding a continuous path that will drive the robot from the start to the goal location avoiding collisions with obstacles. Based on the Simple Genetic Algorithm (AGS) exploration method and the classic A* search algorithm, a hybrid path planning algorithm for multirobots systems is proposed. This algorithm finds the optimal (or near-optimal) collision-free paths of a robot formation from an initial configuration to a final configuration, taking into account the possibility of separation and their subsequent reunification (split&merge). The results of the simulations show that the algorithm is suitable for use in complex environments with obstacles and for a multirobots system.

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Published

2020-10-05

How to Cite

Pereyra, M. E., Araguás, R. G., Pérez Paina, G., & Kulich, M. (2020). Motion planning for a formation of autonomous robots. AJEA (Proceedings of UTN Academic Conferences and Events), (5). https://doi.org/10.33414/ajea.5.698.2020